We have developed a method to automatically detect incidents by detecting abnormal sound events from audio signals recorded in real environments. The proposed method uses the multi-stage Gaussian Mixture Model (GMM), which learns rare sounds using multiple GMMs. In this work, we investigated the relationship between sound environment and detection performance, and found that the performance det...

A Parental Values scale, in which students ranked the top 5 of 10 items in terms of how important they perceived the items as being to their parents, was analyzed using a latent class ranking model. A model with three latent classes was considered adequate, based on the Bayesian information criterion and the interpretability of the results. The three classes were interpreted as consisting of st...

Change-point models are useful for modeling times series subject to structural breaks. For interpretation and forecasting, it is essential to estimate correctly the number of change points in this class of models. In Bayesian inference, the number of changepoints is typically chosen by the marginal likelihood criterion, computed by Chib’s method. This method requires to select a value in the pa...

Speaker change detection or speaker-based segmentation is useful and important in many applications, such as transcribing broadcast news or telephone conversations. It usually serves as a preliminary step prior to speech/speaker recognition. Among various methods proposed in the literature, Bayesian Information Criterion (BIC) based method has been widely used. In this paper, we propose to use ...

Bayesian networks arc now used in enormous fields, for example, system diagnosis, data mining, clustcrings etc. In spite of wide range of their applications, the statistical proper­ tics have not yet been clarified because the models are nonidentifiable and non-regular. In a Bayesian network, the set of parame­ ters for a smaller model is an analytic set with singularities in the parameter spac...

A new approach to Bayesian inference, named the prior-free inference, is introduced for developing objective Bayesian analysis based on information-theoretic approach. This new approach is essentially a Bayesian method but it does not depend on a prior distribution for unknown parameters. Thus, this approach not only has the advantages of the Bayesian approach but also can avoid the difficulty,...

In this paper we focus on an audio segmentation. We present a novel method for robust estimation of decision-thresholds for accurate detection of acoustic change points in continuous audio streams. In standard segmentation procedures the decisionthresholds are usually set in advance and need to be tuned from development data. In the presented approach we tried to remove a need for using pre-det...

We construct a probabilistic coherence measure for information sets which determines a partial coherence ordering. This measure is applied in constructing a criterion for expanding our beliefs in the face of new information. A number of idealizations are being made which can be relaxed by an appeal to Bayesian Networks.

Speaker segmentation systems usually have problems detecting short segments, which causes the number of deletions to be high and therefore harming the performance of the system. This is a complication when it comes to segmenting multimedia information such as movies and TV shows, where dialogs among characters are very common. In this paper a modification of the BIC algorithm is presented, whic...